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Parallel, distributed and GPU computing technologies in single-particle electron microscopy

M. Schmeisser, B. C. Heisen, M. Luettich, B. Busche, F. Hauer, T. Koske, K. H. Knauber, H. Stark
Max Planck Institute for Biophysical Chemistry, Germany
Acta Crystallographica Section D: Biological Crystallography, Vol. 65, No. 7. (01 July 2009), pp. 659-671.

@article{schmeisser2009parallel,

   title={Parallel, distributed and GPU computing technologies in single-particle electron microscopy},

   author={Schmeisser, M. and Heisen, B.C. and Luettich, M. and Busche, B. and Hauer, F. and Koske, T. and Knauber, K.H. and Stark, H.},

   journal={Acta Crystallographica Section D: Biological Crystallography},

   volume={65},

   number={7},

   pages={659–671},

   issn={0907-4449},

   year={2009},

   publisher={International Union of Crystallography}

}

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Most known methods for the determination of the structure of macromolecular complexes are limited or at least restricted at some point by their computational demands. Recent developments in information technology such as multicore, parallel and GPU processing can be used to overcome these limitations. In particular, graphics processing units (GPUs), which were originally developed for rendering real-time effects in computer games, are now ubiquitous and provide unprecedented computational power for scientific applications. Each parallel-processing paradigm alone can improve overall performance; the increased computational performance obtained by combining all paradigms, unleashing the full power of today’s technology, makes certain applications feasible that were previously virtually impossible. In this article, state-of-the-art paradigms are introduced, the tools and infrastructure needed to apply these paradigms are presented and a state-of-the-art infrastructure and solution strategy for moving scientific applications to the next generation of computer hardware is outlined.
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